{"id":"W2131962053","doi":"10.1002/jmri.24648","title":"Principles of T<sub>2</sub>*‐weighted dynamic susceptibility contrast MRI technique in brain tumor imaging","year":2014,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":146,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Manitoba","funders":"Amgen; Takeda Oncology; National Institutes of Health; Sanofi; Bayer HealthCare; National Center for Research Resources; Georgia Clinical and Translational Science Alliance; Teva Pharmaceutical Industries; Southern California Clinical and Translational Science Institute; Biogen; Radiological Society of North America; Bracco Diagnostics","keywords":"Grading (engineering); Magnetic resonance imaging; Brain tumor; Medicine; Dynamic contrast; Radiology; Neuroimaging; Perfusion scanning; Dynamic contrast-enhanced MRI; Nuclear medicine; Medical physics; Perfusion; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001970014,0.0005656355,0.002930915,0.0007504289,0.00005831214,0.00003072093,0.0005289127,0.0001409271,0.00002731736],"category_scores_gemma":[0.0005321633,0.0004632768,0.0007251041,0.0007159497,0.0003725434,0.0001681925,0.0001420092,0.001416347,0.000003582489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00050975,"about_ca_system_score_gemma":0.0006628112,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001068212,"about_ca_topic_score_gemma":0.00001326964,"domain_scores_codex":[0.9952313,0.0002543093,0.002911136,0.0005399375,0.0005365754,0.0005266992],"domain_scores_gemma":[0.9954651,0.0005273576,0.002514552,0.0008111162,0.0004821678,0.0001997118],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004378861,0.0001940858,0.0005083753,0.004432867,0.000007584181,0.0002037206,0.00002108923,0.000002699943,0.004247969,0.0001796181,0.0002110183,0.9899472],"study_design_scores_gemma":[0.001127819,0.0002461419,0.001310683,0.05421256,0.0004495396,0.003609492,0.00003700923,0.001523314,0.001238876,0.0007951942,0.9349359,0.0005135235],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0002808326,0.9444139,0.05202506,0.0007272345,0.00006889329,0.001992862,0.00003430961,0.00005402475,0.0004028613],"genre_scores_gemma":[0.002259825,0.9446482,0.05241429,0.0001548682,0.0001528611,0.0001731772,0.00001765155,0.0001169884,0.00006215942],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9894336,"threshold_uncertainty_score":0.9997819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01388634503426912,"score_gpt":0.325120722905917,"score_spread":0.3112343778716479,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}